Purpose: This study leverages social network analysis (SNA) to visualise the way students interacted with online resources and uses the data obtained from SNA as features for supervised machine learning algorithms to predict whether a student will successfully complete a course. Design/methodology/approach: The exploration and visualisation of the…

The focus of this study was on identifying patterns of student behavior to support data-informed decision-making which would then improve the learning experience and learning outcomes of online English language courses. Learning analytics approach (or more specifically cluster analysis) was used to identify engagement patterns in online learning.…

We study learning outcome prediction for online courses. Whereas prior work has focused on semester-long courses with frequent student assessments, we focus on short-courses that have single outcomes assigned by instructors at the end. The lack of performance data and generally small enrollments makes the behavior of learners, captured as they…

Using data for decision-making is critical for schoolwide leadership teams and has been shown to enhance both social and academic outcomes for students (Faria et al., 2017). Using data effectively, however, requires that teams have a clear vision about the type of data, format of data presentation, and process for using data. To avoid expending…

As more of commerce, entertainment, communication, and learning are occurring over the Web, the amount of data online activities generate is skyrocketing. Commercial entities have led the way in developing techniques for harvesting insights from this mass of data for use in identifying likely consumers of their products, in refining their products…